Book Image

Elasticsearch Essentials

Book Image

Elasticsearch Essentials

Overview of this book

With constantly evolving and growing datasets, organizations have the need to find actionable insights for their business. ElasticSearch, which is the world's most advanced search and analytics engine, brings the ability to make massive amounts of data usable in a matter of milliseconds. It not only gives you the power to build blazing fast search solutions over a massive amount of data, but can also serve as a NoSQL data store. This guide will take you on a tour to become a competent developer quickly with a solid knowledge level and understanding of the ElasticSearch core concepts. Starting from the beginning, this book will cover these core concepts, setting up ElasticSearch and various plugins, working with analyzers, and creating mappings. This book provides complete coverage of working with ElasticSearch using Python and performing CRUD operations and aggregation-based analytics, handling document relationships in the NoSQL world, working with geospatial data, and taking data backups. Finally, we’ll show you how to set up and scale ElasticSearch clusters in production environments as well as providing some best practices.
Table of Contents (18 chapters)
Elasticsearch Essentials
Credits
About the Author
Acknowledgments
About the Reviewer
www.PacktPub.com
Preface
Index

Practical considerations for bulk processing


It's awesome to minimize the requests using the search types and bulk APIs we saw in this chapter, but you also need to think that for a large amount of processing to be done by Elasticsearch, you need to take care of resource utilization and control the size of your requests accordingly. The following are some points that will help you while working with the things you have learned in this chapter.

The most important factor to be taken care of is the size of your documents. Fetching or indexing 1 KB of 1,000 documents in a single request is damn easier than 100 KB of 1,000 documents:

  • Multisearch: While querying with multi search requests, you should take care of how many queries you are hitting in a single request. You just can't combine 1,000 queries in a single query and execute them in one go. Also, the number of queries should be minimized according to the complexity of queries. So, you can break your query set into multiple multi-search requests...